It is necessary to estimate channel state information coherently to equalize the received signal in wireless communication systems. The pilot symbol, known at the receiver, aided channel estimator degrades the transmission efficiency because it requires the signal spaces and the energy for the transmission. In this paper, we assume a fixed wireless communication system in line of sight slowly varying channel and propose a new blind channel estimation method without help from the pilot symbol for Orthogonal Frequency Division Multiplexing systems. The proposed estimator makes use of the Expectation-Maximization algorithm and the correlation property among the channel frequency responses by considering the assumed channel environment. By computer simulations, we show that the proposed estimator can asymptotically achieve bit error rate performance by using the ideal channel estimation.

For estimating user's location, Global Navigation Satellite System (GNSS) is very useful. Especially, Global Positioning System (GPS) by USA is very popular. A GPS receiver needs multiple satellites (usually 4 and more satellites). Propagation to the satellites needs line-of-sight. However, in urban area, there are many buildings. Received signals tend to become bad quality. Such signals are often called as non-line-of-sight (NLOS) or multipath signals. The problem is that the receiver cannot get line-of-sight signals from adequate number of the satellites coinstantaneously. This case leads to degradation of estimation quality or impossibility of estimation. In this paper, we will introduce a novel estimation algorithm, which can estimate own position with as low number of satellites as possible. The proposal achieves the estimation by only two satellites. The proposal also uses a traveling distance sensor which is often equipped on vehicles. By recorded satellite data, we will confirm our effectiveness.

We consider how to accurately estimate the position of targets that exist in closed areas such as a room. In the past, arranging the sensors in a straight line would trigger large position estimation errors in the same direction of the straight line. However, this arrangement is useful because of easy setting, wirings, and space limitations. In this paper, we show a novel algorithm which can reduce the error using signals from reflection objects such as walls. The algorithm uses ellipse relations among sensors, targets and reflection points. Using ellipse relations, the algorithm estimates the positions of the reflection points which are assumed to be the locations of the virtual sensors. So in spite of the straight sensor arranging, the sensors are virtually distributed such as surrounding the targets. In this paper, we show the algorithm and error reduction performances as determined from computer simulations.

Wireless full duplex (FD) communication can double the point-to-point throughput. To fully realize the benefits of the FD technique in wireless local area networks (WLANs), it is important to design the medium access control (MAC) protocols for FD communications. In FD MAC protocols, when a node wins the channel contention and transmits a primary transmission, its destination node can start a secondary transmission triggered by the primary transmission. Each secondary transmitter transmits a data frame even if its backoff timer is not zero. However, the backoff scheme in the FD MAC protocols follows the conventional scheme based on the distributed coordination function (DCF). Therefore, the nodes with FD MAC initialize the contention window (CW) size to minimum CW (CWmin) after their successful secondary transmissions. Therefore, CW initialization in the FD MAC causes further collisions at stations (STAs), which degrades network throughput. This paper proposes a novel backoff scheme for FD MAC protocols. In the proposed scheme, the CW size and backoff timer are not initialized but kept the current value after secondary transmissions. The proposed scheme can mitigate frame collisions at STAs and increase FD-transmission opportunity in the network, and then enhance the throughput significantly. This paper presents comprehensive performance evaluation in simulations, including non-saturation and saturation conditions, and co-existence conditions with legacy half duplex (HD) STAs. For performance analysis, this paper establishes Markov-chain models for the proposed scheme. The analytical results show theoretically that the operation of the proposed scheme enhances network throughput. The simulation results and analytical results show the effectiveness of the proposed scheme.

We consider the position estimation system for targets which exist in near wide area. The system has multiple sensors and estimates the position with multiple receivers. In the past, if receivers were arranged on a straight line, the large position error in the same direction of the line is generated. In order to reduce the error, we propose a novel estimation algorithm using transmitter's directivity information. Our system use directional emission made by an array of antennas in a transmitter. In this paper, the error characteristic which should be solved is introduced firstly. After that, our algorithm is presented. Finally the performance of the error reduction is shown by computer simulations. And we also confirm the reduction by experimental trials. The results indicate good reduction of the error.

We focus on forward-looking radar network systems for automotive usages. By using multiple radars, the radar network systems will achieve reliable detection and wide observation area. The forward-looking systems by cameras are famous. In order to realize more reliable safety, the cameras had better be used with other sensing devices such as the radar network. In the radar network, processing of the data, which is derived from the multiple receivers, is important because the processing decides the estimation performance. In this paper, we will introduce our estimation algorithm which focuses on target existence probability and virtual receivers. The performance will be evaluated by simulated targets which are both single point model and 3D target model.

In this letter, we propose a new distance estimation method based on statistical models of a Received Signal Strength (RSS) at the receiver. The conventional distance estimator estimates the distance between the transmitter and the receiver based on the statistical average of the RSS when the receiver obtains instantaneous RSS and an estimate of the hyperparameters which consists of the path loss exponent and so on. However, it is well-known that instantaneous RSS does not always correspond to the average RSS because the RSS varies in accordance with a statistical model. Although the statistical model has been introduced for the hyperparameters estimation and the localization system, the conventional distance estimator has not yet utilized it. We introduce the statistical model to the distance estimator whose expected value of the estimate corresponds to true distance. Our theoretical analysis establishes that the proposed distance estimator is preferable to the conventional one in order to improve accuracy in the expected value of the distance estimate. Moreover, we evaluate the Mean Square Error (MSE) between true distance and the estimate. We provide evidence that the MSE is always proportional to the square of the distance if the estimate of the hyperparameters is ideally obtained.

In wireless sensor networks (WSNs), wireless power transfer (WPT) has been studied as an energy-harvesting technique for prolonging their network lifetime. The WPT can supply power resources to sensor nodes (SNs) wirelessly, however, the reception (harvesting) power at SNs depends on their distance from a WPT equipment (WPTE), leading to the location-dependent non-uniformity in the reception power among SNs. For the fixed-located WPTE, SNs distant from the WPTE suffer from insufficient reception power. To handle this problem, this paper proposes a novel network structure introducing multiple hybrid access points (HAPs), which equip two functions of conventional cluster head function, including data collection and relay transmission, and WPT function. Then, these HAPs take terms providing both functions. By periodically rotating the HAP providing the WPT function, the location of the WPTE can be changed, which reduces the non-uniformity in the SN reception power. Also, this paper proposes a clustering scheme based on the residual power at SNs to reduce their power depletion under the proposed network structure. The evaluation results through computer simulation show that the proposed system reduces the non-uniformity in the SN reception power and the power depletion at the SNs and then improves the data collection rate, compared with the conventional systems.

Motorcycles are driven in a road widely but must be driven carefully because they are easily damaged by obstacles, bumps or potholes in the road. Thus, motorcycle trajectories are valuable for detecting road abnormalities. The trajectories are usually obtained from GPS (Global Positioning System). However, errors often occur in GPS positioning. In this research, we will present a detection idea of the GPS error based on behavior estimation of riders. Moreover, we will propose a novel behavior estimation method.

Radar networks show an interesting potential for safety and comfortable applications such as short-range automotive monitoring system or indoor monitoring. This paper presents our novel estimation algorithm of a target position. Especially we evaluate the performance about estimation accuracy and resistance to ghost targets under multipath environment. In above applications, the robust estimation is needed because the receivers tend to output corrupted measurement data. The corrupted data are mostly generated by multipath, sensitivity of receivers. As a result of computer simulations, our algorithm has fine accuracy and robust detections compared with a popular trilateration algorithm.

Incoming GPS signals through windows can be often observed indoors. However, conventional indoor positioning systems do not use Global Positioning System (GPS) generally because the signals may come in NLOS (Non Line of Sight). In this paper, we propose a positioning method by fingerprinting based on the incoming GPS signals.

The fifth-generation (5G) new radio (NR) standard employs ultra-reliable and low-latency communication (URLLC) to provide real-time wireless interactive capability for the internet of things (IoT) applications. To satisfy the stringent latency and reliability demands of URLLC services, grant-free (GF) transmissions with the K-repetition transmission (K-Rep) have been introduced. However, fading fluctuations can negatively impact signal quality at the base station (BS), leading to an increase in the number of repetitions and raising concerns about interference and energy consumption for IoT user equipment (UE). To overcome these challenges, this paper proposes novel adaptive K-Rep control schemes that employ site diversity reception to enhance signal quality and reduce energy consumption. The performance evaluation demonstrates that the proposed adaptive K-Rep control schemes significantly improve communication reliability and reduce transmission energy consumption compared with the conventional K-Rep scheme, and then satisfy the URLLC requirements while reducing energy consumption.

Location information is meaningful information for future ITS (Intelligent Transport Systems) world. Especially, the accuracy of the information is required because the accuracy decides the quality of ITS services. For realization of high precision positioning, Kinematic positioning technique has been attracting attention. The Kinematic positioning requires the configuration of many positioning parameters. However, the configuration is difficult because optimal parameter differs according to user's environment. In this paper, we will propose an estimation method of optimal parameter according to the environment. Further, we will propose an elimination method of unreliable positioning results. Hereby, we can acquire extensively only the reliable positioning results. By using the actual vehicle traveling data, the ability and the applicable range of the proposed method will be shown. The result will show that our proposed method improves the acquision rate of reliable positioning results and mitigates the acquision rate of the unreliable positioning results.